3 future trends of retail data analytics

Consumers are making more purchases online than ever before, and retailers must adapt to keep ahead of their competition. For many retailers, the pandemic has been an eye-opener, with rapid growth in some product segments and slower growth in others revealing the limitations of their organization’s current operational efficiency. (Research) These revelations are now driving the demand for better visibility into customer demands and behavior. To keep pace with competitors in the industry, retailers must gain a 360° view of their customers, make more informed merchandising decisions, and run operations more efficiently.

Gain a complete view of customers with unified data

Multiple touchpoints ranging from website to support center create a complex web of data compounded by customer interactions on external platforms such as social media. Data from these sources become siloed and “stuck” within different parts of the organization.

Unifying data alleviates that problem by bringing data from disparate sources into a single data warehouse to uncover hidden insights about customer behavior that can increase acquisition and retention. By harnessing historical data to analyze real-time interactions like click streams, log events, and other external sources, retailers can gain valuable insights into customer behavior and customize their experience.

Forecast demand quickly and accurately

Demand forecasting has come to the forefront and tops the list of most important areas for analysis. This trend towards heavy reliance on data has had a sizable boost since the pandemic, which has driven up demand in specific product categories while flattening out others.

Retailers can use GCP to better predict sales, even at the granular level, and see the effect of price promotions on their forecasts. Seamless integration with ERP systems on-premise, in the cloud, or in a hybrid setup makes it possible to take real-world action on those predictions and insights.

Fast and accurate demand forecasting relies on built-in machine learning and analytics. Retailers can rapidly query data with a GCP data warehouse in the cloud, including the machine learning and analytics needed for real-time insights and improvised customer behavior models.

Increase efficiencies across the supply chain

Technologies like IoT and digital shelf tags are giving retailers new data points that provide insight into their products, opening opportunities for more accurately allocating resources.

Data-driven retailers can increase supply chain and operational efficiency in both proactive and reactive situations to reduce costs and more accurately meet customer demand. One example of a proactive measure in 2021 was the rise of curbside pickup, providing services where customers need them. Live connections between the cloud environment, the point of sale, and inventory tracking can help boost efficiencies and build resilience into the supply chain.

Over 67% of U.S. shoppers check if items are in stock before visiting the store, and without real-time inventory data, the supply chain cannot adjust, and customers get left in the dark. With accurate historical and real-time data, retailers can gain the visibility to better respond to current demands and make the adjustments necessary to fulfill the customer’s requirements.

GCP BigQuery Case study: The Home Depot

The Home Depot (THD) is the world's largest home-improvement chain, with more than 2,200 stores. Much of their growth is fueled by data, but their on-premises data warehouse was under stress from the increasing data and increasingly complex use cases. Even with detailed planning, one complex upgrade resulted in three days of downtime, and even after this upgrade, the extra capacity was quickly exhausted. 

THD decided to move to Google Cloud's BigQuery for its cloud enterprise data warehouse. Data storage increased from 450 terabytes to 15 petabytes, improving the insights from deeper analysis of years of data. At the same time, performance on all use cases increased, with a finance use case dropping from 14 days to 3 days, and a supply chain use case going from 8 hours to only 5 minutes.

Start to Get Data Insights Today! 

Forward-thinking retailers know that data is the trump card for gaining a competitive advantage. It is no longer a nice-to-have business option: it’s imperative for survival. Gain all the valuable data insights your business needs today with Google Cloud and its trusted partner CloudMile. 

CloudMile, Google Cloud Managed Service Provider (MSP) has been empowering businesses to accelerate digital transformation through cloud technology and machine learning. Partnering with CloudMile, you can get the most out of your data and shorten the time to business success! 

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